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- research-articleAugust 2024
Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data MiningPages 1004–1015https://doi.org/10.1145/3637528.3671759Job recommender systems are crucial for aligning job opportunities with job-seekers in online job-seeking. However, users tend to adjust their job preferences to secure employment opportunities continually, which limits the performance of job ...
- research-articleAugust 2024
RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes
KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data MiningPages 4047–4058https://doi.org/10.1145/3637528.3671711In the realm of education, both independent learning and group learning are esteemed as the most classic paradigms. The former allows learners to self-direct their studies, while the latter is typically characterized by teacher-directed scenarios. Recent ...
- research-articleAugust 2024
A survey on large language models for recommendation
- Likang Wu,
- Zhi Zheng,
- Zhaopeng Qiu,
- Hao Wang,
- Hongchao Gu,
- Tingjia Shen,
- Chuan Qin,
- Chen Zhu,
- Hengshu Zhu,
- Qi Liu,
- Hui Xiong,
- Enhong Chen
AbstractLarge Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive amounts of ...
- research-articleAugust 2024JUST ACCEPTED
CARL: Unsupervised Code-Based Adversarial Attacks for Programming Language Models via Reinforcement Learning
ACM Transactions on Software Engineering and Methodology (TOSEM), Just Accepted https://doi.org/10.1145/3688839Code based adversarial attacks play a crucial role in revealing vulnerabilities of software system. Recently, pre-trained programming language models (PLMs) have demonstrated remarkable success in various significant software engineering tasks, ...
- research-articleAugust 2024
Perceptual authentication hashing for digital images based on multi-domain feature fusion
AbstractIn recent decades, numerous perceptual authentication hashing schemes have been proposed for image content authentication. However, most of these schemes are based on a single spatial or transform domain, and they fail to provide satisfactory ...
Highlights- A new robust perceptual hashing scheme for image authentication is proposed.
- Multi-domain feature fusion strategy is exploited for hash sequence generation.
- The channel filter and attention module are designed in frequency domain.
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- research-articleJuly 2024JUST ACCEPTED
Learning Compressed Artifact for JPEG Manipulation Localization Using Wide-Receptive-Field Network
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Just Accepted https://doi.org/10.1145/3678883JPEG image manipulation localization aims to accurately classify and locate tampered regions in JPEG images. Existing image manipulation localization schemes usually consider diverse data streams of spatial domain, e.g. noise inconsistency and local ...
- research-articleJuly 2024
FollowAKOInvestor: Stock recommendation by hearing voices from all kinds of investors with machine learning
Expert Systems with Applications: An International Journal (EXWA), Volume 249, Issue PBhttps://doi.org/10.1016/j.eswa.2024.123522AbstractAs an increasing number of investors share their opinions on social networks, a critical challenge is to provide advice and assistance in making well-informed investment decisions by considering enormous online sentiments. A typical way is to ...
Highlights- A novel machine learning-based method is proposed to aggregate investor sentiments.
- Sentiments from various investors matter for the stock recommendation.
- Applying machine learning to follow various investors boosts performance.
- research-articleJuly 2024
AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations
SIGIR '24: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information RetrievalPages 1242–1252https://doi.org/10.1145/3626772.3657724Collaborative filtering methods based on graph neural networks (GNNs) have witnessed significant success in recommender systems (RS), capitalizing on their ability to capture collaborative signals within intricate user-item relationships via message-...
- ArticleAugust 2024
Super-Node Generation for GNN-Based Recommender Systems: Enhancing Distant Node Integration via Graph Coarsening
AbstractIn the realm of recommender systems, Graph Neural Network based collaborative filtering has emerged as a leading approach. This method represents user-item interactions as a bipartite graph, facilitating the extraction of user and item embeddings ...
- research-articleJuly 2024
DoBMark: A double-branch network for screen-shooting resilient image watermarking
Expert Systems with Applications: An International Journal (EXWA), Volume 246, Issue Chttps://doi.org/10.1016/j.eswa.2024.123159AbstractThe dramatic changes in cross-media information transmission modes, especially screen-shooting, have made traditional robust image watermarking for digital channels less resistant to various physical noises from the real world. To address this ...
- research-articleMay 2024
HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection
WWW '24: Proceedings of the ACM Web Conference 2024Pages 4479–4488https://doi.org/10.1145/3589334.3645718Knowledge tracing (KT) is a crucial task in online learning, aimed at tracing and predicting each student's knowledge states throughout their learning process. Over the past decade, it has garnered widespread attention due to it provides the potential ...
- research-articleMay 2024
Collaboration-Aware Hybrid Learning for Knowledge Development Prediction
WWW '24: Proceedings of the ACM Web Conference 2024Pages 3976–3985https://doi.org/10.1145/3589334.3645326In recent years, the rise of online Knowledge Management Systems (KMSs) has significantly improved work efficiency in enterprises. Knowledge development prediction, as a critical application within these online platforms, enables organizations to ...
- research-articleApril 2024
Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph
ACM Transactions on Information Systems (TOIS), Volume 42, Issue 4Article No.: 110, Pages 1–28https://doi.org/10.1145/3651158Career mobility analysis aims at understanding the occupational movement patterns of talents across distinct labor market entities, which enables a wide range of talent-centered applications, such as job recommendation, labor demand forecasting, and ...
- research-articleAugust 2024
Screen-shot and Demoiréd image identification based on DenseNet and DeepViT
Expert Systems with Applications: An International Journal (EXWA), Volume 240, Issue Chttps://doi.org/10.1016/j.eswa.2023.122580AbstractHow to identify the screen-shot image is an important branch of image source forensics. Although the physical feature of moiré patterns may be left after LCD recapture operation, this feature may also be well concealed with the development of ...
Highlights- Improve the generality of the screen-shot image detection task.
- Propose a network dedicated to the demoiréing algorithm identification.
- Analyze the features of DenseNet and DeepViT in demoiréd image forensics.
- Has a detection ...
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- research-articleJune 2024
DHU-Net: High-capacity binary data hiding network based on improved U-Net
AbstractDue to limited data-hiding capacity and low extraction accuracy, most existing data hiding schemes have difficulty in high capacity hiding and lossless extraction of binary data. This paper proposes a novel binary data hiding network (DHU-Net) ...
Highlights- DHU-Net is proposed to achieve lossless binary data hiding and extracting.
- High-capacity data hiding is achieved under ensuring stego image quality.
- DHU-Net has certain robustness, can resist compress and noise attacks.
- ...
- research-articleFebruary 2024
Universal screen-shooting robust image watermarking with channel-attention in DCT domain
Expert Systems with Applications: An International Journal (EXWA), Volume 238, Issue PFhttps://doi.org/10.1016/j.eswa.2023.122062AbstractIn this paper, we propose a universal screen-shooting robust image watermarking scheme, which can be used to embed extractable information into on-screen images for copyright protection or additional information acquisition. Specifically, to ...
- research-articleMay 2024
DUIANet: A double layer U-Net image hiding method based on improved Inception module and attention mechanism
Journal of Visual Communication and Image Representation (JVCIR), Volume 98, Issue Chttps://doi.org/10.1016/j.jvcir.2023.104035AbstractImage hiding is the process of hiding secret image into cover image, and revealing secret image from steganographic image. However, the quality of generated images and the ability to resist steganalysis detection of steganographic image can be ...
Highlights- We propose a novel double-layer U-Net structure that can fully extract and fuse image features, generate high-quality image, and still have good performance when hiding multiple images.
- Our method improves the anti-steganalysis ability ...
- research-articleJanuary 2024
RDGT: Enhancing Group Cognitive Diagnosis With Relation-Guided Dual-Side Graph Transformer
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 36, Issue 7Pages 3429–3442https://doi.org/10.1109/TKDE.2024.3352640Cognitive diagnosis has been widely recognized as a crucial task in the field of computational education, which is capable of learning the knowledge profiles of students and predicting their future exercise performance. Indeed, considerable research ...
- research-articleDecember 2023
Reversible PRNU anonymity for device privacy protection based on data hiding
Expert Systems with Applications: An International Journal (EXWA), Volume 234, Issue Chttps://doi.org/10.1016/j.eswa.2023.121017AbstractIn this paper, we propose a method of protecting a device from being identified with the images captured by it. This method can suppress the device-related fingerprint, i.e., PRNU, in an image via modifying it in the domain of integer wavelet ...
- research-articleMarch 2024
Quality guided reversible data hiding with contrast enhancement
Journal of King Saud University - Computer and Information Sciences (JKSUCIS), Volume 35, Issue 10https://doi.org/10.1016/j.jksuci.2023.101808Graphical abstractDisplay Omitted
Highlights- Consider the effect of peak pair selection on image quality.
- Select the optimal peak pair from the candidates dynamically.
- Design a weighting sum function with the metric score of each peak pair as input.
- Design an optimizer ...
Reversible data hiding with contrast enhancement (RDH-CE) enables contrast enhancement of the image and lossless recovery of host image after embedded data extraction. Although the current RDH-CE methods are effective in enhancing carrier images ...